Research on New Green Camouflage Pigments

2011 ◽  
Vol 282-283 ◽  
pp. 666-669 ◽  
Author(s):  
Zhi Yi Hu ◽  
Hong Shu Chen
Keyword(s):  
Ferric Oxide ◽  
Spectral Reflectance ◽  
Green Pigment ◽  
Pigment Synthesis ◽  
Original Mixture

A pigment of Al2O3-CoO system has been prepared as a new green pigment for camouflage materials. The effect of the CoO content in the original mixture on the spectral reflectance of the pigment has been evaluated. The temperature condition of the pigment synthesis has been found. The pigment of Al2O3-CoO system has been modified as green camouflage pigment by ferric oxide, and the camouflage effect has also been estimated. The result shows that the pigment based on Al2O3-CoO system, as a substitute of Cr2O3, is a successful camouflage pigment.

scholarly journals Isolation and molecular characterization of the Aspergillus nidulans wA gene.

Genetics ◽  
1990 ◽  
Vol 126 (1) ◽  
pp. 73-79 ◽  
Author(s):  
M E Mayorga ◽  
W E Timberlake
Keyword(s):  
Aspergillus Nidulans ◽  
Wild Type Strain ◽  
Nuclear Dna ◽  
Cosmid Library ◽  
Wild Type ◽  
Green Pigment ◽  
Mrna Accumulation ◽  
Pigment Synthesis ◽  
Regulatory Loci

Abstract The walls of Aspergillus nidulans conidia contain a green pigment that protects the spores from damage by ultraviolet light. At least two genes, wA and yA, are required for pigment synthesis: yA mutants produce yellow spores, wA mutants produce white spores, and wA mutations are epistatic to yA mutations. We cloned wA by genetic complementation of the wA3 mutation with a cosmid library containing nuclear DNA inserts from the wild-type strain. The wA locus was mapped to an 8.5-10.5-kilobase region by gene disruption analysis. DNA fragments from this region hybridized to a 7500 nucleotide polyadenylated transcript that is absent from hyphae and mature conidia but accumulates during conidiation beginning when pigmented spores first appear. Mutations in the developmental regulatory loci brlA, abaA, wetA and apsA prevent wA mRNA accumulation. By contrast, yA mRNA fails to accumulate only in the brlA- and apsA- mutants. Thus, the level of wA transcript is regulated during conidiophore development and wA activation requires genes within the central pathway regulating conidiation.

Green Pigment From Chromate of Barium

1879 ◽  
Vol 8 (194supp) ◽  
pp. 3094-3094
Author(s):  
Thos. Douglas
Keyword(s):  
Green Pigment

Skin Chromophore Estimation from Mobile Selfie Images using Constrained Independent Component Analysis

2020 ◽  
Vol 2020 (14) ◽  
pp. 357-1-357-6
Author(s):  
Luisa F. Polanía ◽  
Raja Bala ◽  
Ankur Purwar ◽  
Paul Matts ◽  
Martin Maltz
Keyword(s):  
Independent Component Analysis ◽  
Spectral Reflectance ◽  
Source Separation ◽  
Principal Component ◽  
Component Analysis ◽  
Previous Method ◽  
Independent Component ◽  
Light Transport ◽  
Camera Model ◽  
Constrained Independent Component Analysis

Human skin is made up of two primary chromophores: melanin, the pigment in the epidermis giving skin its color; and hemoglobin, the pigment in the red blood cells of the vascular network within the dermis. The relative concentrations of these chromophores provide a vital indicator for skin health and appearance. We present a technique to automatically estimate chromophore maps from RGB images of human faces captured with mobile devices such as smartphones. The ultimate goal is to provide a diagnostic aid for individuals to monitor and improve the quality of their facial skin. A previous method approaches the problem as one of blind source separation, and applies Independent Component Analysis (ICA) in camera RGB space to estimate the chromophores. We extend this technique in two important ways. First we observe that models for light transport in skin call for source separation to be performed in log spectral reflectance coordinates rather than in RGB. Thus we transform camera RGB to a spectral reflectance space prior to applying ICA. This process involves the use of a linear camera model and Principal Component Analysis to represent skin spectral reflectance as a lowdimensional manifold. The camera model requires knowledge of the incident illuminant, which we obtain via a novel technique that uses the human lip as a calibration object. Second, we address an inherent limitation with ICA that the ordering of the separated signals is random and ambiguous. We incorporate a domain-specific prior model for human chromophore spectra as a constraint in solving ICA. Results on a dataset of mobile camera images show high quality and unambiguous recovery of chromophores.

A Flying Gray Ball Multi-illuminant Image Dataset for Color Research

2020 ◽  
Vol 64 (5) ◽  
pp. 50411-1-50411-8
Author(s):  
Hoda Aghaei ◽  
Brian Funt
Keyword(s):  
Machine Vision ◽  
Spectral Reflectance ◽  
Color Constancy ◽  
Ground Truth ◽  
Practical Approach ◽  
Post Processing ◽  
Illumination Estimation ◽  
Processing Step ◽  
Image Dataset

Abstract For research in the field of illumination estimation and color constancy, there is a need for ground-truth measurement of the illumination color at many locations within multi-illuminant scenes. A practical approach to obtaining such ground-truth illumination data is presented here. The proposed method involves using a drone to carry a gray ball of known percent surface spectral reflectance throughout a scene while photographing it frequently during the flight using a calibrated camera. The captured images are then post-processed. In the post-processing step, machine vision techniques are used to detect the gray ball within each frame. The camera RGB of light reflected from the gray ball provides a measure of the illumination color at that location. In total, the dataset contains 30 scenes with 100 illumination measurements on average per scene. The dataset is available for download free of charge.

The Spectral Reflectance Properties of Soil Structural Crusts in the 1.2- to 2.5-μm Spectral Region

2003 ◽  
Vol 67 (1) ◽  
pp. 289 ◽  
Author(s):  
E. Ben-Dor ◽  
N. Goldlshleger ◽  
Y. Benyamini ◽  
M. Agassi ◽  
D. G. Blumberg
Keyword(s):  
Spectral Region ◽  
Spectral Reflectance ◽  
Properties Of Soil
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